Sparse-WAM: Accelerating World Action Models via Action-Guided Sparse Imagination
World-action models (WAMs) leverage pretrained video models to improve generalization in robot control by jointly predicting future visual states and actions. This capability comes at a substantial inference cost, as dense future-frame tokens are repeatedly processed during denoising. Prior methods address this by toke...
Xin-Ling Xie, Hao-Dong Wang, Jia-Zhi Mi et al.
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